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Thomas Lymburn
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Consistency in echo-state networks
T Lymburn, A Khor, T Stemler, DC Corrêa, M Small, T Jüngling
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (2), 2019
552019
The reservoir’s perspective on generalized synchronization
T Lymburn, DM Walker, M Small, T Jüngling
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (9), 2019
392019
Reservoir computing with swarms
T Lymburn, SD Algar, M Small, T Jüngling
Chaos: An Interdisciplinary Journal of Nonlinear Science 31 (3), 2021
152021
Reconstruction of complex dynamical systems from time series using reservoir computing
T Jüngling, T Lymburn, T Stemler, D Corrêa, D Walker, M Small
2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2019
112019
Consistency hierarchy of reservoir computers
T Jüngling, T Lymburn, M Small
IEEE Transactions on Neural Networks and Learning Systems 33 (6), 2586-2595, 2021
62021
Learned emergence in selfish collective motion
SD Algar, T Lymburn, T Stemler, M Small, T Jüngling
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (12), 2019
62019
Quantifying robustness and capacity of reservoir computers with consistency profiles
T Lymburn, T Jüngling, M Small
International Conference on Artificial Neural Networks, 447-458, 2020
42020
Model Calibration and Validation From A Statistical Inference Perspective
S Ting, T Lymburn, T Stemler, Y Sun, M Small
arXiv preprint arXiv:2309.08562, 2023
12023
Parameter estimation for Gipps’ car following model in a Bayesian framework
S Ting, T Lymburn, T Stemler, Y Sun, M Small
Physica A: Statistical Mechanics and its Applications 639, 129671, 2024
2024
Consistency capacity of reservoir computers
T Jüngling, T Lymburn, M Small
arXiv preprint arXiv:2105.13473, 2021
2021
Beyond the Echo State Property-Generalised Synchronisation and Consistency in Reservoir Computers
T Lymburn
2021
Echo-state networks in nonlinear dynamical systems
T Lymburn, T Jüngling, T Stemler, D Corrêa, M Small
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Articles 1–12